Instructions to use Dewa/dog_emotion_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dewa/dog_emotion_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Dewa/dog_emotion_v2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Dewa/dog_emotion_v2") model = AutoModelForImageClassification.from_pretrained("Dewa/dog_emotion_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (5a1bffef4d15c1c4de706d93f9cb18dbb13f7396) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>dde0c87
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Update README.md
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dog-emotion detector
it is a simple image-classification model fine-tuned from "google/vit-base-patch16-224-in21k" using kaggle dog emotion dataset can tell is the dog angry,sad,relaxed,happy --this is can come handy if we want to monitor dog behaviour from a video and image to understand about our four-legs buddy9c2d68c -
Training in progress, epoch 3
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Training in progress, epoch 2
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Training in progress, epoch 1
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initial commit
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